Abstract:

The intestinal microbiota is a complex microbial ecosystem that occupies the human host and is essential for health and well-being. More specifically, it plays a dominant role in nutrition, development, metabolism, pathogen resistance and the regulation of immune response. Recent technological advances have aided our discovery of these vastly diverse microbial communities and their importance to host physiology has been unveiled. However, the mechanisms that control this complex ecosystem are yet to be fully elucidated.

Experimental evidence supports the presence of bistable abundance distributions in the intestinal microbiota. Some bacterial taxa exist in either a high or low abundance state with decreased stability observed at the intermediate abundance range. Since bistability is relatively difficult to measure in the human gut microbiota (due to the lack of longitudinal data made readily available), bistability can be inferred from observations of bimodality in vastly accessible static data. In addition to this, the quantification of the unstable region observed at the intermediate abundance range and the assessment of state stability and transitions provides us with further evidence to support the concept alternative stable states within the human gut.

Here, bimodality detection, intermediate stability and multi-state modelling have been implemented upon high-resolution microarray and next generation sequencing microbiota profiling data in attempt to identify bistable groups in sub-communities of intestinal microbes.

The aim of this thesis is to identify novel bistable taxa along with the validation of pre-existing bistable groups. It is also assess how bistability is best observed in this complex nonlinear dynamical system. The bistable taxa appearing here have provided us with candidates for the manipulation of the intestinal microbiota for desired health outcomes. Furthermore, their robustness also serves as an indicator of the overall ecosystem state providing great diagnostic potential.